Digital Product Owner, Research Decision Intelligence

Sanofi•Cambridge, MA

1d•$133,500 - $192,833•Hybrid

About The Position

The Digital In-Silico Research team is a key innovation engine within Digital R&D, dedicated to pioneering next-generation digital products that reshape how R&D discovers and develops new medicines. We harness AI, machine learning, and computational modeling to build transformative in-silico solutions delivering predictive insights, streamlining workflows, and turning data into decisive action. Within this team, the Data Visualization & Decision Support product line translates complex scientific data and model outputs into intuitive, high-impact tools that enable scientists and decision-makers to act with speed and confidence. We are looking for a passionate, driven Digital Product Owner to join the Data Visualization & Decision Support product line within the In-Silico Research team, taking ownership of a critical digital product that empowers scientists to make faster, more confident, data-driven decisions. If you thrive at the intersection of science and technology, equally at home in a user discovery conversation with a bench scientist and a technical refinement session with an ML engineer and take pride in shipping solutions that change how research gets done, this role is for you. As Product Owner, you will own end-to-end delivery of one or more data visualization and decision support products, working in agile cross-functional pods alongside data scientists, ML engineers, UX/UI designers, and front-end developers. You will define the product vision, manage the backlog, translate complex scientific and computational requirements into actionable user stories, and drive adoption of tools that become indispensable to researchers' daily workflows. You will partner with the Product Line Owner to ensure your products deliver coherent, high-value experiences across the portfolio. Your success will be measured not just by what you ship, but by the measurable impact on scientific productivity and the pace of drug discovery. Ready to push the limits of what’s possible? Join Sanofi in one of our corporate functions and you can play a vital part in the performance of our entire business while helping to make an impact on millions around the world.

Requirements

Bachelor's degree required in Life Sciences, Computational Biology, Bioinformatics, Computer Science, or a related field.
A minimum of 5+ years of experience in product management, product ownership, or related roles within pharmaceutical R&D, biotech, or life sciences.
Proven track record delivering digital products in scientific or technical environments.
Strong experience with data visualization tools is required.
Experience working in agile cross-functional teams (Scrum, Kanban) and managing product backlogs
Demonstrated ability to conduct user research and translate findings into actionable product requirements
Solid understanding of drug discovery workflows and the challenges of computational and experimental research
Understanding of databases, data pipelines, data quality, and cloud-based platforms
Experience with product management and collaboration tools such as JIRA, Confluence, Figma, or Miro
Exceptional ability to listen to scientists and end users—and turn what you hear into products they want to use
Strong scientific translation skills: you can hold a credible conversation with a computational biologist and a business leader in the same afternoon
Structured problem-solver who can navigate ambiguity, manage competing priorities, and make decisive trade-offs
Clear, confident communicator who can influence without authority and build alignment across functions
Change management mindset: patient, strategic, and persistent in driving adoption in scientific organizations
Collaborative spirit and genuine curiosity—you want to understand the science, not just manage the backlog
Growth mindset and enthusiasm for the rapidly evolving AI/ML landscape in drug discovery

Nice To Haves

Master's or PhD is a plus
Familiarity with electronic lab notebooks (ELNs) including Benchling and Genedata Biologics is a plus.
Snowflake experience preferred.
Background spanning both wet-lab biology and computational/data science
Familiarity with data visualization tools, AI/ML concepts and their applications in life sciences (model types, outputs, uncertainty quantification, validation)
Experience with platform migrations, technology transitions, or new capability onboarding is a plus
Familiarity with life science data browsing platforms such as Spotfire, D360, or equivalent tools is desirable but not a must.
Portfolio demonstrating scientific interface, data visualization, or platform projects
Knowledge of regulatory considerations for AI/ML tools in pharmaceutical R&D
Understanding of API integration, data pipeline concepts, and how backend architecture impacts user experience
Track record of facilitating design-thinking workshops and co-creation sessions with diverse stakeholder groups
Experience in large pharma environments with complex organizational structures and governance processes

Responsibilities

Own and prioritize the product vision, roadmap, and backlog for your product line, ensuring clear alignment with scientific priorities and Digital R&D strategy
Write clear, well-scoped user stories, acceptance criteria, and success metrics grounded in real scientist workflows
Lead agile ceremonies (sprint planning, backlog grooming, retrospectives) and drive iterative product delivery with cross-functional pods
Make sound, data-informed prioritization decisions—balancing new feature development, technical debt, and user feedback
Establish regular touchpoints with software development teams to validate technical requirements and ensure optimal solution architecture
Drive products through governance stage gates with clear go/no-go recommendations, business cases, and executive summaries
Hands-on experience with life science data browsing and visualization platforms such as Spotfire and D360. Familiarity with electronic lab notebooks (ELNs) including Benchling and Genedata Biologics is a plus.
Ability to query databases directly, with Snowflake experience preferred.
Able to interpret what a data entity means in a biological context not just technically, but scientifically by asking the right questions of domain experts.
Capable of tracing data lineage end-to-end: from point of entry in an ELN, through a data warehouse such as Snowflake, to its visualization and consumption in tools like Spotfire. This systems-level understanding is essential for writing precise, unambiguous requirements.
Experienced in using diagrams including business process flows, scientific workflows, and data flow diagrams to align cross-functional and cross-cultural stakeholders.
Conduct continuous user research with R&D scientists to deeply understand their workflows, bottlenecks, data needs, and interface requirements
Champion user-centered design principles throughout the product lifecycle, partnering with UX/UI designers to create intuitive, scientifically accurate interfaces
Lead usability testing sessions, synthesize feedback, and rapidly iterate to improve user experience
Independently sketch wireframes and low-fidelity mockups to communicate product vision to design and engineering teams.
Build and execute targeted user adoption strategies for platform launches and transitions
Monitor usage metrics and user satisfaction continuously, using data to guide product evolution
Identify and proactively address barriers to adoption across different business functions and user personas
Demonstrate product value through compelling scientific use cases and measurable outcomes
Build strong partnerships with R&D scientists, computational biologists, data scientists, and ML engineers to ensure products meet real scientific needs.
Collaborate with the Product Line Owner on portfolio strategy, prioritization, and resource allocation
Facilitate co-creation workshops, ideation sessions, and requirements gathering with diverse stakeholder groups
Communicate product progress, value delivered, and adoption metrics to stakeholders and leadership with clarity and confidence; manage competing expectations and negotiate trade-offs with transparency and sound judgment